A method, device and equipment for processing a trustworthy reward business based on blockchain

Abstract

The embodiments of this specification disclose a trusted reward business processing method, device and equipment based on blockchain, which is applied to a blockchain server. The solution includes: obtaining the user's real-person authentication information from the reward server of the reward platform and uploading it to the chain; after a reward event occurs on the reward platform, obtaining the record information of the reward event from the reward server and uploading it to the chain, and the record information indicates the corresponding rewarding user and the rewarded user; running an abnormal reward monitoring model, and inspecting one or more reward events on the reward platform based on the information that has been uploaded to the chain to determine whether there are suspicious reward events; if so, reporting the suspicious reward event to the regulatory end for abnormal confirmation.

Description

Technical Field

[0001] This specification relates to the field of blockchain technology, and in particular to a blockchain-based trusted reward business processing method, device, and equipment. Background Art

[0002] In the existing technology, the server content of many reward platforms is not public and is easy to tamper with, making it impossible to effectively monitor reward events on the reward platforms. Therefore, it is difficult to discover suspicious reward events involving illegal profit transfer during the reward process. Summary of the Invention

[0003] One or more embodiments of this specification provide a blockchain-based trusted reward service processing method, device, and apparatus to solve the following technical problems:

[0004] The server contents of many reward platforms are not public and are easy to tamper with, making it impossible to effectively monitor reward events on the reward platforms. As a result, it is difficult to detect suspicious reward events involving illegal profit transfer during the reward process.

[0005] One or more embodiments of this specification adopt the following technical solutions:

[0006] One or more embodiments of this specification provide a blockchain-based trusted reward service processing method, which is applied to a blockchain server. The method includes:

[0007] Obtain the user's real-person authentication information from the reward platform's reward server and upload it to the blockchain;

[0008] After a reward event occurs on the reward platform, the record information of the reward event is obtained from the reward server and uploaded to the blockchain, wherein the record information indicates the corresponding rewarding user and the rewarded user;

[0009] Run an abnormal reward monitoring model to inspect one or more reward events on the reward platform based on the information uploaded to the chain to determine whether there are any suspicious reward events;

[0010] If so, the suspicious reward event will be reported to the regulatory end for abnormal confirmation.

[0011] One or more embodiments of this specification provide a blockchain-based trusted reward service processing device, which is applied to a blockchain server. The device includes:

[0012] The first acquisition unit obtains the user's real-person authentication information from the reward platform's reward server and uploads it to the blockchain;

[0013] A second acquisition unit, after a reward event occurs on the reward platform, obtains record information of the reward event from the reward server and uploads it to the blockchain, wherein the record information indicates the corresponding rewarding user and the rewarded user;

[0014] The inspection unit runs an abnormal reward monitoring model and inspects one or more reward events on the reward platform based on the information uploaded to the chain to determine whether there are any suspicious reward events;

[0015] The reporting unit reports the suspicious reward event to the regulatory end for abnormality confirmation.

[0016] One or more embodiments of this specification provide a blockchain-based trusted reward service processing device, which is applied to a blockchain server and includes:

[0017] at least one processor; and,

[0018] a memory communicatively connected to the at least one processor; wherein,

[0019] The memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to:

[0020] Obtain the user's real-person authentication information from the reward platform's reward server and upload it to the blockchain;

[0021] After a reward event occurs on the reward platform, the record information of the reward event is obtained from the reward server and uploaded to the blockchain, wherein the record information indicates the corresponding rewarding user and the rewarded user;

[0022] Run an abnormal reward monitoring model to inspect one or more reward events on the reward platform based on the information uploaded to the chain to determine whether there are any suspicious reward events;

[0023] If so, the suspicious reward event will be reported to the regulatory end for abnormal confirmation.

[0024] One or more embodiments of this specification provide a non-volatile computer storage medium storing computer-executable instructions, wherein the computer-executable instructions are configured to:

[0025] Obtain the user's real-person authentication information from the reward platform's reward server and upload it to the blockchain;

[0026] After a reward event occurs on the reward platform, the record information of the reward event is obtained from the reward server and uploaded to the blockchain, wherein the record information indicates the corresponding rewarding user and the rewarded user;

[0027] Run an abnormal reward monitoring model to inspect one or more reward events on the reward platform based on the information uploaded to the chain to determine whether there are any suspicious reward events;

[0028] If so, the suspicious reward event will be reported to the regulatory end for abnormal confirmation.

[0029] At least one of the above technical solutions adopted in the embodiments of this specification can achieve the following beneficial effects: the embodiments of this specification upload the acquired real-person authentication information of the user and the record information of the reward event to the chain. Since the information on the chain has the characteristic of being tamper-proof, when the reward events of the reward platform are subsequently inspected based on the information on the chain, the inspection results will be more accurate and reliable. At the same time, the embodiments of this specification can more timely and effectively monitor the reward events of the reward platform by running the abnormal reward monitoring model to determine whether the reward event is suspicious. In addition, when it is determined that there is an event that can be rewarded, the embodiments of this specification can quickly report the suspicious reward event to the supervision end, so as to speed up the processing of suspicious reward events as much as possible. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the embodiments of this specification or the technical solutions in the prior art, the following briefly introduces the drawings required for the embodiments or the description of the prior art. Obviously, the drawings described below are only some of the embodiments described in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without inventive work. In the drawings:

[0031] Figure 1 A flowchart of a blockchain-based trusted reward service processing method provided in one or more embodiments of this specification;

[0032] Figure 2 A flowchart of a trusted reward method based on blockchain provided in one or more embodiments of this specification;

[0033] Figure 3 A schematic diagram of the structure of a blockchain-based trusted reward service processing device provided in one or more embodiments of this specification;

[0034] Figure 4 A schematic diagram of the structure of a blockchain-based trusted reward business processing device provided for one or more embodiments of this specification. DETAILED DESCRIPTION

[0035] The embodiments of this specification provide a blockchain-based trusted reward business processing method, device, and equipment.

[0036] In order to better illustrate the solution of the embodiment of this specification, the following is a detailed description mainly from the perspective of bribery on the reward platform:

[0037] Bribery and corruption through reward platforms are detrimental to the reputation of the reward platforms. The reward platforms are unable to promptly monitor and report any bribery that occurs, and they may also bear corresponding responsibilities.

[0038] To help those skilled in the art better understand the technical solutions in this specification, the following will provide a clear and complete description of the technical solutions in the embodiments of this specification, in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of this specification, not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this specification without creative work should fall within the scope of protection of this specification.

[0039] Figure 1 This is a flowchart of a trusted tipping service processing method based on blockchain, provided in one or more embodiments of this specification. This method can be applied to a public tipping chain server, which can be integrated with live streaming software on various tipping platforms to prevent users from engaging in bribery through tipping in live streaming rooms within the software, thereby maintaining a positive atmosphere on the tipping platform. Certain input parameters or intermediate results in the process can be manually adjusted to improve accuracy.

[0040] It should be noted that the reward public chain server can be a server with blockchain properties, and the data uploaded to the reward public chain server cannot be tampered with.

[0041] The method steps of the embodiment of this specification are as follows:

[0042] S102: Obtain the user’s real-person authentication information from the reward platform’s reward server and upload it to the chain.

[0043] In the embodiments of this specification, users may include viewers of the live broadcast room and the host of the live broadcast room. The viewers of the live broadcast room can perform reward events on the host. The user needs to enter the user's real-person authentication information in the designated reward client. The reward client mentioned in this case is the live broadcast software that needs to be authenticated. Only then can the reward events generated by the reward client be uploaded to the chain and supervised by the supervisory end. Among them, the reward client mentioned in this case is subordinate to the reward platform. After the user downloads and installs the reward client, the host will broadcast live or the audience will watch the host's performance.

[0044] Before users can execute a tipping event on the tipping client, they need to undergo identity verification. When criminals use tipping to bribe or receive bribes, the relevant identity information can be used to trace the true identities of both the tipper and the recipient.

[0045] In real life, most users are authenticated by real-name authentication, which is a verification and review of the authenticity of user information, and helps to establish a complete and reliable Internet credit foundation.

[0046] Among them, real-person authentication can rely on biometric technologies such as optical character recognition (OCR) technology, liveness detection, and face comparison to verify the authenticity of user identity information when authenticating the user, which can better verify that the user is a real person and the user is himself.

[0047] Putting the user's real-person authentication information on the chain means uploading the user's real-person authentication information to the reward public chain server through the reward server. The reward public chain server is used to record the real-person authentication information of all users, making it easier to identify bribery and corruption in subsequent reward events.

[0048] S104: After a reward event occurs on the reward platform, the record information of the reward event is obtained from the reward server and uploaded to the chain. The record information indicates the corresponding rewarding user and the rewarded user.

[0049] The tipping user can be the viewer who initiated the tipping event, and the tipped user can be the live streamer in the reward platform's live streaming room. After a viewer in the live streaming room on the reward platform initiates a tipping event to the streamer, the reward event record information is obtained from the reward server and uploaded to the reward public chain server. The record information of the reward event is tamper-proof, facilitating subsequent query and verification.

[0050] To query a specific tipping event, the public chain server receives a query request with a user ID from the evidence collection client, which can be the query client. The query request is triggered by the supervisory authority. Based on the user ID, the public chain server is then queried for records corresponding to the corresponding tipping event. The user can be the tipping user and / or the tipped user. Finally, the public chain server returns the query results to the evidence collection client as evidence.

[0051] To prevent criminals from using reward platforms to bribe or accept bribes, a pre-trained abnormal reward monitoring model can be used to monitor the live broadcast rooms on each reward platform in real time, thereby solving the problem of difficulty in real-time monitoring of reward platforms. The corresponding operations can be completed by executing the following S106.

[0052] S106: Run the abnormal reward monitoring model and inspect one or more reward events on the reward platform based on the information uploaded to the chain to determine whether there are any suspicious reward events.

[0053] The reward monitoring model run by the reward public chain server can be a monitoring model based on neural network training. The model is trained with a large amount of data about reward events and can accurately inspect reward events.

[0054] The on-chain information mentioned at this time can be the user's real-person authentication information. The embodiment of this specification can inspect the reward events on the reward platform through the relationship between the rewarding user and the rewarded user.

[0055] In the embodiments of the specification, a smart contract can be used to run an abnormal reward monitoring model whenever a set condition is met. The set condition here is the various situations mentioned above, that is, the information on the chain is the user's real-person authentication information. Then, through the operation of the abnormal reward monitoring model, the record information of one or more reward events on the chain is traversed and detected. Traversing the record information of one or more reward events on the chain can be done by using the abnormal reward monitoring model to find the record information of one or more suspicious reward events among all the record information of reward events.

[0056] In addition, the information uploaded to the chain can also be reward events that have been determined to contain the nature of bribery and corruption. Subsequently, the characteristics of bribery and corruption reward events can be extracted through the abnormal reward monitoring model, and the reward events on the reward platform can be inspected based on the characteristics of bribery and corruption reward events. That is, the reward events on the reward platform can be analyzed for their characteristics. If they contain the characteristics of bribery and corruption reward events, it can be determined that bribery and corruption may exist in this reward event.

[0057] In the embodiments of this specification, the record information of the reward event can also indicate the time and reward gift of the corresponding reward event. When detecting the record information of one or more reward events that have been chained, it can be specifically determined, based on the record information of the reward event, whether the multiple reward events corresponding to the same rewarding user or the same rewarded user occur too frequently and / or the reward gift value is too high, so as to determine whether there is a suspicious reward event. For example, in a live broadcast room of a certain reward platform, the rewarding user a rewards the rewarded user b once or multiple times with a large number of virtual gifts, which means that the live broadcast room may be found to have bribery and corruption. In addition, if multiple rewarding users in the same live broadcast room reward the rewarded user with a large number of virtual gifts in a short period of time, it can also be determined that the live broadcast room may be found to have bribery and corruption. After determining that the live broadcast room may have bribery and corruption, the live broadcast room can be temporarily designated as a suspicious live broadcast room and reported to the regulatory authorities for further determination.

[0058] Before determining whether multiple reward events corresponding to the same rewarding user or the same rewarded user occur too frequently and / or the value of the reward gifts is too high, the embodiments of this specification can also determine, based on the set risk quantity threshold, whether the number of audience users in the live broadcast session to which the reward event to be detected belongs is too small. If the number of audience users is too small and the events are too frequent and / or the value of the reward gifts is too high, the probability of bribery is higher, and the risk quantity threshold can be set to 10 people. For example, in a live broadcast room on a certain reward platform, there are only 3 viewers, and these 3 viewers have initiated a large number of gift rewards, or one of the viewers has initiated a large number of gift rewards. These situations are all possible bribery and the live broadcast room can be temporarily designated as a suspicious live broadcast room and reported to the regulatory authorities for further determination.

[0059] In addition, before determining whether multiple reward events corresponding to the same rewarding user or the same rewarded user occur too frequently and / or the reward gifts are too valuable, the embodiments of this specification can also identify the content of the live broadcast of the anchor in the live broadcast room to determine whether the live broadcast content of the anchor is normal. If the live broadcast content of the anchor is not normal, and is too frequent and / or the reward gifts are too valuable, there is a high probability of bribery. Whether it is normal live broadcast content can be identified based on the live broadcast content of most normal anchors. If bribery is present, most of them will not conduct normal live broadcasts, but will simply open a live broadcast room to receive rewards. Since it is only for bribery, the time the anchor opens the live broadcast may also be relatively short. For example, in a live broadcast room on a certain reward platform, the anchor does not broadcast any live content, and the reward events in the live broadcast room occur too frequently and / or the reward gifts are too valuable, it can be determined that there may be bribery in the live broadcast room.

[0060] Furthermore, in addition to the above-mentioned inspection methods, attention should also be paid to the multiple flows of gift rewards. That is, when bribery occurs in a live broadcast room, the first gift reward is normal. In the subsequent process, the host who receives the reward transfers the reward, and the transfer can be carried out in batches. To address the above problem, the embodiments of this specification can detect bribery through the following scheme:

[0061] Determine the rewarded user and reward gift of the reward event, treat the rewarded user as the first rewarded user, and then obtain the secondary flow information of the reward gift after it is obtained by the first rewarded user and upload it to the chain, so as to record the secondary flow information of the reward gift and facilitate subsequent tracing.

[0062] When detecting the record information of one or more reward events that have been uploaded to the chain, you can first determine whether the secondary flow information indicates that the reward gift flows from the first rewarded user to the second rewarded user. Then, determine the popularity of the first rewarded user and the second rewarded user on the reward platform respectively, and then determine whether the popularity of the first rewarded user is greater than that of the second rewarded user, and the difference between the two is greater than the set degree. If so, it can be determined that there is an abnormality in the reward event.

[0063] In the above process, if the popularity of the first rewarded user is greater than that of the second rewarded user, it can be said that the first rewarded user is a popular anchor, and when the anchor receives a large number of rewards, it is a normal reward event. If the first rewarded user forwards the reward received to the second rewarded user with lower popularity, this behavior is suspicious. At this time, if the popularity difference between the first rewarded user and the second rewarded user is large, it can be said that the popularity of the second rewarded user is relatively low, and the behavior of the first rewarded user forwarding the reward gift to the second rewarded user is very suspicious, and it can be determined that there is an abnormality in the reward event. At the same time, the popularity of the second rewarded user can also be determined separately. If the popularity of the second rewarded user is lower than the preset level, it can be said that the second rewarded user is not a popular anchor, and is unlikely to be an anchor that the reward platform needs to support. At this time, the first rewarded user forwards a large number of gifts to the second rewarded user, and it can be determined that there is an abnormality in the reward event.

[0064] Furthermore, when examining the recorded information of one or more rewarding events that have been uploaded to the blockchain, the rewarding user and the rewarded user can be identified based on the recorded information. The uploaded real-person authentication information can include the corresponding user's work information. Subsequently, based on the user's work information in the real-person authentication information and a pre-established work relationship model, it can be predicted whether there is a risk of profit transfer between the rewarding user and the rewarded user. This risk of profit transfer corresponds to illegal relationships involving reward platforms, such as bribery and the legalization of illegal benefits.

[0065] The working relationship model of the embodiment of this specification can determine the various working relationships between users. For example, if the rewarding user works at Company A and the rewarded user also works at Company A, the working relationship model can determine that the rewarding user and the rewarded user are in the same company. For another example, if the rewarding user works at Company A and the rewarded user works at Company B, a subsidiary of Company A, the working relationship model can also determine that the rewarding user and the rewarded user are in the same company. Being in the same company may involve bribery. For another example, if the rewarding user works at Company A and the rewarded user works at Company B, which has a cooperative relationship with Company A, the working relationship model can also determine that the rewarding user and the rewarded user are related to each other, and related companies may also involve bribery.

[0066] S108: If yes, the suspicious reward event will be reported to the regulatory side for abnormal confirmation.

[0067] Before traversing and detecting the record information of one or more reward events that have been uploaded to the chain, the embodiments of this specification can first obtain the information of the risk user, and then query the record information of one or more reward events corresponding to the risk user based on the information of the risk user, so as to be used for the subsequent traversal and detection of the record information of one or more reward events that have been uploaded to the chain. If it is determined that there is a suspicious reward event among the traversed and detected reward events, the audience users in the live broadcast room to which the suspicious reward event belongs are determined, and based on the audience users in the live broadcast room, the risk user relationship network including the risk user is determined. Finally, the risk user relationship network and the reward event can be reported to the regulatory end for abnormal confirmation.

[0068] By identifying the risky user network including risky users, all persons involved in bribery activities can be investigated subsequently, without missing any person who has committed a crime.

[0069] If it is determined that there are no suspicious reward events among the traversed and detected reward events, the embodiment of this specification continues to inspect subsequent reward events to better maintain the legal operation of the entire reward platform and eliminate illegal reward events in the reward platform.

[0070] The illegal behavior of benefit transfer refers to the legal conversion of illegal benefits. The embodiments of this specification are intended to prevent lawbreakers from legalizing illegal benefits through reward platforms.

[0071] The embodiments of this specification primarily target illegal activities involving the use of reward platforms to transfer benefits. This is not limited to bribery and the legalization of illegal benefits, but can also include asset transfers. In this case, the embodiments of this specification can also use the above-mentioned method to conduct inspections to determine whether there are suspicious reward incidents. If so, the suspicious reward incidents are reported to the regulatory authorities for abnormal confirmation.

[0072] If criminals exploit livestreaming, bribers can complete the entire bribery process by tipping or sending gifts to the bribed. Current tipping mechanisms are difficult to investigate because the content of livestream servers is not public, and the content of rewards posted on current tipping platforms is easily tampered with. Therefore, tipping platforms need to be adjusted to ensure trustworthy tipping, making livestream tipping transparent and reliable, and eliminating bribery and the legalization of illegal gains.

[0073] This specification provides a blockchain-based trusted reward method. The specific flow chart can be found in Figure 2 This method is divided into four parts: reward client, reward server, reward public chain server and query end (for example, evidence monitoring end, collection end, etc.). Among them:

[0074] The reward client is responsible for receiving rewards from the host and for the audience to reward the host; the reward server records the identity, amount, time and device information of the rewarder for the user; the reward public chain server is used to upload all reward records to the chain, start inspections, and automatically discover that rewards can be given; the query terminal is used to query the reward record of a person through the platform user name (ID) or ID card, which is for police verification

[0075] 1: The reward client sends the real-person authentication of the audience and the anchor to the reward server; 1.1: The reward server sends the user's real-person authentication information and ID to the reward public chain server to complete the chain operation; 2: When the audience of the reward client rewards the designated anchor, the corresponding reward record is sent to the reward server; 2.1: The reward server sends the rewarder, the rewarded person, the reward amount, the reward time and the reward location to the reward public chain server to complete the chain operation; 3: If a reward is allowed, the query end uses the ID card or name of the rewarder or the rewarded person to initiate a query to the reward public chain server; 3.1: The reward server traverses the queried reward and reward records; 3.2: The reward server returns the result to the query end as evidence.

[0076] Automatic inspections can also be performed on the public reward chain server. Specifically, 3.3: Based on clues provided by the police and existing rules discovered by R&D, customized inspection models are published. Model rules include: 1. Large amounts of rewards in a short period of time; 2. Large amounts of rewards from a single person or a small number of people; 3.4: The published monitoring model is loaded through the smart contract at regular intervals and then traversed through transactions. Because it is on the blockchain, data from any node can be traversed; 3.5: Suspicious rewards are automatically detected based on the configured model and reported to facilitate supervision or police confirmation.

[0077] The above solutions provided in the embodiments of this specification have the following features:

[0078] 1. It can proactively identify whether the reward is bribery, illegal profiteering, or genuine rewards based on live broadcast content;

[0079] 2. You can check the credible reward records of the rewarder or the rewarded person at any time;

[0080] 3. We can find out whether these two people have a record of rewarding or bribing based on the clues provided by the police;

[0081] 4. If there is illegal tipping, the risky user network can be analyzed from the paths of tipping and receiving tips.

[0082] 5. The record information of reward events cannot be tampered with.

[0083] Figure 3 A schematic structural diagram of a blockchain-based trusted reward business processing device provided for one or more embodiments of this specification, the device includes: a first acquisition unit 302, a second acquisition unit 304, an inspection unit 306 and a reporting unit 308.

[0084] The first acquisition unit 302 obtains the user's real-person authentication information from the reward server of the reward platform and uploads it to the blockchain;

[0085] After a reward event occurs on the reward platform, the second obtaining unit 306 obtains the record information of the reward event from the reward server and uploads it to the chain. The record information indicates the corresponding rewarding user and the rewarded user;

[0086] The inspection unit 306 runs an abnormal reward monitoring model and inspects one or more reward events on the reward platform based on the information uploaded to the chain to determine whether there are any suspicious reward events;

[0087] If yes, the reporting unit 308 reports the suspicious reward event to the supervisory end for abnormality confirmation.

[0088] Furthermore, the device also includes:

[0089] A receiving unit, receiving a query request carrying a user identifier sent from an evidence collection terminal;

[0090] The first query unit queries the chain for record information corresponding to a corresponding reward event based on the user identifier;

[0091] The evidence unit returns the query results to the evidence collection end as evidence.

[0092] Furthermore, the inspection unit 306 executes the abnormal reward monitoring model and inspects multiple reward events on the reward platform based on the information uploaded to the chain, specifically including:

[0093] Through smart contracts, the abnormal reward monitoring model is run whenever the set conditions are met;

[0094] By running the abnormal reward monitoring model, the record information of one or more reward events that have been uploaded to the chain is traversed and detected.

[0095] Furthermore, before the inspection unit 306 performs traversal and inspection of the record information of one or more reward events that have been uploaded to the chain, the device further includes:

[0096] The third acquisition unit acquires information of risky users;

[0097] The second query unit queries the record information of one or more reward events corresponding to the risky user based on the risky user's information for traversal and detection;

[0098] After the inspection unit 306 determines whether there is a suspicious reward event, the device further includes:

[0099] A user determination unit, if the determination result is yes, determines the audience users in the live broadcast room to which the suspicious tipping event belongs;

[0100] The relationship network determining unit determines a risk user relationship network including the risk user based on the audience users at the same venue.

[0101] Furthermore, the record information also indicates the time of the corresponding reward event and the reward gift. The inspection unit 306 performs the following inspections:

[0102] Based on the recorded information, determine whether multiple reward events corresponding to the same rewarding user or the same rewarded user occur too frequently and / or the value of the reward gifts is too high.

[0103] Furthermore, before the inspection unit 306 determines whether multiple rewarding events corresponding to the same rewarding user or the same rewarded user occur too frequently and / or the reward gifts are too valuable, the apparatus further includes:

[0104] The quantity determination unit determines, based on a set risk quantity threshold, that the number of viewer users of the live broadcast session to which the reward event to be detected belongs is too small.

[0105] Furthermore, the device also includes:

[0106] A determination unit, determining a rewarded user of a rewarding event as a first rewarded user;

[0107] The fourth acquisition unit acquires the secondary flow information of the reward gift after it is received by the first rewarded user and uploads it to the blockchain;

[0108] The inspection unit 306 performs the inspection further including:

[0109] Determining that the secondary flow information indicates that the reward gift flows from the first rewarded user to the second rewarded user;

[0110] Determine the popularity of the first tipped user and the second tipped user on the tipping platform respectively;

[0111] Determine whether the popularity of the first rewarded user is greater than that of the second rewarded user, and whether the difference between the two is greater than a set degree.

[0112] Furthermore, the real-person authentication information uploaded to the chain includes the corresponding user's work information. The inspection unit 306 performs the following inspections:

[0113] Determine the tipping user and tipped user of the corresponding tipping event based on the recorded information;

[0114] Based on real-person authentication information and a pre-built work relationship model, it is predicted whether there is a risk of interest transfer between the rewarding user and the rewarded user.

[0115] Figure 4 A schematic diagram of the structure of a blockchain-based trusted reward service processing device provided for one or more embodiments of this specification, applied to a blockchain server, includes:

[0116] at least one processor; and,

[0117] a memory communicatively connected to at least one processor; wherein,

[0118] The memory stores instructions executable by at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to:

[0119] Obtain the user's real-person authentication information from the reward platform's reward server and upload it to the blockchain;

[0120] When a reward event occurs on the reward platform, the reward event record information is obtained from the reward server and uploaded to the blockchain. The record information indicates the corresponding rewarding user and the rewarded user;

[0121] Run an abnormal reward monitoring model to inspect one or more reward events on the reward platform based on the information uploaded to the chain to determine whether there are any suspicious reward events;

[0122] If so, the suspicious reward event will be reported to the regulatory end for abnormal confirmation.

[0123] One or more embodiments of this specification provide a non-volatile computer storage medium storing computer-executable instructions, wherein the computer-executable instructions are configured to:

[0124] Obtain the user's real-person authentication information from the reward platform's reward server and upload it to the blockchain;

[0125] When a reward event occurs on the reward platform, the reward event record information is obtained from the reward server and uploaded to the blockchain. The record information indicates the corresponding rewarding user and the rewarded user;

[0126] Run an abnormal reward monitoring model to inspect one or more reward events on the reward platform based on the information uploaded to the chain to determine whether there are any suspicious reward events;

[0127] If so, the suspicious reward event will be reported to the regulatory end for abnormal confirmation.

[0128] In the 1990s, technological improvements could be clearly distinguished as either hardware improvements (for example, improvements to circuit structures like diodes, transistors, and switches) or software improvements (improvements to process flows). However, with the advancement of technology, many process flow improvements can now be considered direct improvements to hardware circuit structures. Designers almost always create the corresponding hardware circuit structure by programming the improved process flow into the hardware circuit. Therefore, it cannot be said that a process flow improvement cannot be implemented using physical hardware modules. For example, a programmable logic device (PLD), such as a field programmable gate array (FPGA), is an integrated circuit whose logical function is determined by user programming. Designers can "integrate" a digital system on a PLD by programming it themselves, without having to hire a chip manufacturer to design and manufacture a dedicated integrated circuit chip. Moreover, nowadays, instead of manually fabricating integrated circuit chips, this programming is mostly performed using software called a "logic compiler." This is similar to the software compilers used during program development. Before compilation, the original code must be written in a specific programming language, called a Hardware Description Language (HDL). There are many types of HDL, including ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, and RHDL (Ruby Hardware Description Language). Currently, the most commonly used are VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art will also understand that simply by programming a method flow in one of these hardware description languages and then programming it into an integrated circuit, a hardware circuit that implements the logic method flow can be easily obtained.

[0129] The controller can be implemented in any suitable manner. For example, the controller can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, an application-specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320. The memory controller can also be implemented as part of the memory control logic. Those skilled in the art will also appreciate that, in addition to implementing the controller purely in computer-readable program code, the controller can also be implemented in the form of logic gates, switches, an application-specific integrated circuit, a programmable logic controller, an embedded microcontroller, etc. by logically programming the method steps. Therefore, such a controller can be considered a hardware component, and the means for implementing the various functions included therein can also be considered as structures within the hardware component. Alternatively, the means for implementing the various functions can be considered both a software module implementing the method and a structure within the hardware component.

[0130] The systems, devices, modules, or units described in the above embodiments may be implemented by computer chips or entities, or by products having certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0131] For the convenience of description, the above devices are described as being divided into various units according to their functions. Of course, when implementing this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0132] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems, or computer program products. Thus, the embodiments of this specification may take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware. Furthermore, the embodiments of this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0133] This specification is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of this specification. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0134] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0135] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0136] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0137] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0138] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0139] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0140] This specification may be described in the general context of computer-executable instructions, such as program modules, executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, and the like that perform specific tasks or implement specific abstract data types. This specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media, including storage devices.

[0141] The various embodiments in this specification are described in a progressive manner. Similar portions between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from the other embodiments. In particular, the device, apparatus, and non-volatile computer storage medium embodiments are generally similar to the method embodiments, so their descriptions are relatively simplified. For relevant details, refer to the descriptions of the method embodiments.

[0142] The foregoing description of this specification describes specific embodiments. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0143] The foregoing description is merely one or more embodiments of this specification and is not intended to limit this specification. It will be apparent to those skilled in the art that various modifications and variations may be made to one or more embodiments of this specification. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of one or more embodiments of this specification are intended to be within the scope of the claims of this specification.

Claims

1. A blockchain-based trusted reward service processing method, applied to a blockchain server, comprising: Obtain the user's real-person authentication information from the reward platform's reward server and upload it to the blockchain; After a reward event occurs on the reward platform, the record information of the reward event is obtained from the reward server and uploaded to the blockchain, wherein the record information indicates the corresponding rewarding user and the rewarded user; Run an abnormal reward monitoring model, and inspect one or more reward events on the reward platform based on the information already on the chain to determine whether there are any suspicious reward events. Specifically, the model runs the abnormal reward monitoring model through a smart contract whenever a set condition is met. Through the operation of the abnormal reward monitoring model, the recorded information of one or more reward events on the chain is traversed and inspected; the inspection is carried out based on the relationship between the rewarding user and the rewarded user, which can be a business relationship or a superior-subordinate relationship. If so, the suspicious reward event will be reported to the regulatory end for abnormal confirmation; Before traversing and detecting the record information of one or more reward events that have been uploaded to the chain, the method further includes: Obtain information about risky users; According to the information of the risky user, query the record information of the one or more reward events corresponding to the risky user for traversal and detection; After determining whether there is a suspicious reward event, the method further includes: If the determination result is yes, then determine the audience users in the live broadcast room to which the suspicious reward event belongs; Determining a risky user relationship network including the risky user based on the same audience users; The method further comprises: Determine the rewarded user of the reward event as the first rewarded user; Obtaining secondary flow information of the reward gift after it is received by the first rewarded user and uploading it to the blockchain; The detection also includes: Determining that the secondary flow information indicates that the reward gift flows from the first rewarded user to the second rewarded user; Determining the popularity of the first rewarded user and the second rewarded user on the reward platform respectively; Determine whether the popularity of the first rewarded user is greater than that of the second rewarded user, and whether the difference between the two is greater than a set degree. If so, determine that there is an abnormality in the reward event.

2. The method of claim 1, further comprising: Receiving a query request carrying a user identifier from an evidence collection terminal; According to the user ID, query on the chain whether there is record information corresponding to the corresponding reward event; The query result is returned to the evidence collection end as evidence.

3. The method according to claim 1, wherein the recorded information further indicates the time of the corresponding reward event and the reward gift, and the detection specifically comprises: Based on the recorded information, determine whether multiple rewarding events corresponding to the same rewarding user or the same rewarded user occur too frequently and / or whether the value of the reward gifts is too high.

4. The method of claim 3, wherein before determining whether multiple tipping events corresponding to the same tipping user or the same tipped user occur too frequently and / or the value of the tipping gifts is too high, the method further comprises: According to the set risk quantity threshold, it is determined that the number of viewer users of the live broadcast session to which the reward event to be detected belongs is too small.

5. In the method according to claim 1, the real-person authentication information uploaded to the chain includes the corresponding user's work information, and the detection specifically includes: Determine the rewarding user and the rewarded user corresponding to the reward event according to the recorded information; Based on the real-person authentication information and a pre-built work relationship model, it is predicted whether there is a risk relationship of interest transfer between the rewarding user and the rewarded user.

6. A blockchain-based trusted reward service processing device, applied to a blockchain server, comprising: The first acquisition unit obtains the user's real-person authentication information from the reward platform's reward server and uploads it to the blockchain; A second acquisition unit, after a reward event occurs on the reward platform, obtains record information of the reward event from the reward server and uploads it to the blockchain, wherein the record information indicates the corresponding rewarding user and the rewarded user; The inspection unit runs an abnormal reward monitoring model and inspects one or more reward events on the reward platform based on the information on the chain to determine whether there are any suspicious reward events. Specifically, the inspection unit runs the abnormal reward monitoring model through a smart contract whenever a set condition is met. Through the operation of the abnormal reward monitoring model, the record information of one or more reward events on the chain is traversed and detected; the inspection is performed based on the relationship between the rewarding user and the rewarded user, which can be a business relationship or a superior-subordinate relationship. If so, the reporting unit reports the suspicious reward event to the supervisory end for abnormality confirmation; Before the inspection unit performs the traversal and detection of the record information of one or more reward events that have been uploaded to the chain, the device further includes: The third acquisition unit acquires information of risky users; A second query unit, based on the information of the risky user, queries the record information of the one or more reward events corresponding to the risky user for traversal and detection; After the inspection unit performs the determination of whether there is a suspicious reward event, the device further includes: A user determining unit, if the determination result is yes, determines the audience users in the live broadcast room to which the suspicious reward event belongs; a relationship network determining unit, for determining a risk user relationship network including the risk user based on the audience users; The device further comprises: a determining unit, determining a rewarded user of the reward event as a first rewarded user; A fourth acquisition unit acquires secondary flow information of the reward gift after it is received by the first rewarded user and uploads it to the blockchain; The inspection unit further includes: Determining that the secondary flow information indicates that the reward gift flows from the first rewarded user to the second rewarded user; Determining the popularity of the first rewarded user and the second rewarded user on the reward platform respectively; Determine whether the popularity of the first rewarded user is greater than that of the second rewarded user, and whether the difference between the two is greater than a set degree. If so, determine that there is an abnormality in the reward event.

7. The apparatus of claim 6, further comprising: A receiving unit, receiving a query request carrying a user identifier sent from an evidence collection terminal; A first query unit queries on the chain whether there is record information corresponding to a corresponding reward event according to the user identifier; The evidence unit returns the query result to the evidence collection end as evidence.

8. The device according to claim 6, wherein the recorded information further indicates the time of the corresponding reward event and the reward gift, and the inspection unit performs the inspection specifically comprising: Based on the recorded information, determine whether multiple rewarding events corresponding to the same rewarding user or the same rewarded user occur too frequently and / or whether the value of the reward gifts is too high.

9. The apparatus according to claim 8, wherein before the inspection unit performs the step of determining whether multiple rewarding events corresponding to the same rewarding user or the same rewarded user occur too frequently and / or the reward gifts are too valuable, the apparatus further comprises: The quantity determination unit determines, based on a set risk quantity threshold, that the number of viewer users of the live broadcast session to which the reward event to be detected belongs is too small.

10. The apparatus according to claim 6, wherein the real-person authentication information uploaded to the chain includes work information of the corresponding user, and the inspection unit performs the inspection specifically comprising: Determine the rewarding user and the rewarded user corresponding to the reward event according to the recorded information; Based on the real-person authentication information and a pre-built work relationship model, it is predicted whether there is a risk relationship of interest transfer between the rewarding user and the rewarded user.

11. A blockchain-based trusted reward service processing device, applied to a blockchain server, comprising: at least one processor; as well as, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to: Obtain the user's real-person authentication information from the reward platform's reward server and upload it to the blockchain; After a reward event occurs on the reward platform, the record information of the reward event is obtained from the reward server and uploaded to the blockchain, wherein the record information indicates the corresponding rewarding user and the rewarded user; Run an abnormal reward monitoring model, and inspect one or more reward events on the reward platform based on the information already on the chain to determine whether there are any suspicious reward events. Specifically, the model runs the abnormal reward monitoring model through a smart contract whenever a set condition is met. Through the operation of the abnormal reward monitoring model, the recorded information of one or more reward events on the chain is traversed and inspected; the inspection is carried out based on the relationship between the rewarding user and the rewarded user, which can be a business relationship or a superior-subordinate relationship. If so, the suspicious reward event will be reported to the regulatory end for abnormal confirmation; Before traversing and detecting the record information of one or more reward events on the chain, the following steps are further performed: Obtain information about risky users; According to the information of the risky user, query the record information of the one or more reward events corresponding to the risky user for traversal and detection; After determining whether there is a suspicious reward event, the following steps are also performed: If the determination result is yes, then determine the audience users in the live broadcast room to which the suspicious reward event belongs; Determining a risky user relationship network including the risky user based on the same audience users; Also includes: Determine the rewarded user of the reward event as the first rewarded user; Obtaining secondary flow information of the reward gift after it is received by the first rewarded user and uploading it to the blockchain; The detection also includes: Determining that the secondary flow information indicates that the reward gift flows from the first rewarded user to the second rewarded user; Determining the popularity of the first rewarded user and the second rewarded user on the reward platform respectively; Determine whether the popularity of the first rewarded user is greater than that of the second rewarded user, and whether the difference between the two is greater than a set degree. If so, determine that there is an abnormality in the reward event.

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